#Pentaho data integration generate rows how to#
#Pentaho data integration generate rows software#
#Pentaho data integration generate rows free#

But since we don't know exact count or maybe even names or types, we cannot do it. The last step is done from GUI by defining field names and types. In general, we need to get the input row, put our values there and adjust meta-data.

#Pentaho data integration generate rows how to#

It will create processRow method and some example code how to resize row from the input and send it back to PDI. I like to start working on a class by generating Main body from Code Snippits - Common use. How do I work for Pentaho Pentaho Data Integration (PDI) tutorial. In our example, we will read one field with string containing names and use this string to create multiple new fields per each name in User Defined Java Class step. Values will be assigned to different fields otherwise. Of course, these two rows have to be aligned. PDI knows this way how to interpret and cast values. This row with values is accompanied by another row of the same size with field meta-data. In order to insert new fields to stream, we need to understand how PDI handles them. New fields had to be added to stream dynamically and since this isn't a common use case, it required some investigation.Р”Р‡ortunately, PDI has not only a high number of different functions, but it is extendable using step with custom Java or JavaScript logic.

A request was to make one complex transformation configurable using JSON. This can depend on a different set of input data or external JSON with configuration. The trouble starts when I want to dynamically create fields and I don't know beforehand their count, names or types. If I want to enhance the stream of rows with new column, I have to define the name and type in ETL. To filter rows (remove the rows from the output for example) set the transStatus variable as follows: transStatus CONTINUETRANSFORMATION if (/ add your condition here /) transStatus SKIPTRANSFORMATION All rows matching the specified condition are removed from the output. Pentaho Data Integration (Kettle) Pentaho can take many file types as input, but it can connect to only two SaaS platforms: Google Analytics and Salesforce. Developers can create new connectors using Informatica Connector Toolkit. If I want to process CSV file with two columns, I have to define those two columns (and value types) in the step which loads the file. The only data lake destination it supports is Microsoft Azure SQL Data Lake. For those who didn't work with PDI, let me give you an example. It is only logical that we also have to define the data structure. In this case the values originate from a Generate Rows step for.

#Pentaho data integration generate rows software#

At the end of the day, you need to tell the software how to transform the data. Variable: Variables can be used throughout Pentaho Data Integration, including in. But you could probably say something similar about other ETL tools. It runs on-premises rather than as a SaaS application.

#Pentaho data integration generate rows free#

The software comes in a free community edition and a subscription-based enterprise edition. Let's say that the ETL tool PDI isn't very suitable for dynamic data processing. About Pentaho Data Integration (Kettle) Pentaho, a subsidiary of Hitachi Vantara, is an open source platform for data integration and analytics.